Methodologic issues relating to the use of STARHS to determine HIV incidence: The Ontario experience

Transcription

1 Methodologic issues relating to the use of STARHS to determine HIV incidence: The Ontario experience Robert S. Remis MD, MPH Department of Public Health Sciences, University of Toronto National HIV Prevention Conference Centers for Disease Control and Prevention Atlanta, GA, USA, June 14, 2005

2 Introduction HIV incidence a critical indicator in monitoring the HIV epidemic Reflects success in reducing HIV transmission Informs policy makers in marshalling resources and program planners in targeting and evaluating preventive interventions

3 Introduction Serodiagnostic data useful for HIV surveillance Less sensitive ( detuned or STARHS) assay of confirmed HIV-positive specimens identifies recently infected persons (e.g. previous 4 months) Can be used to calculate HIV incidence, usually very difficult to measure

4 Potential settings for application of STARHS Dedicated seroepidemiologic studies HIV diagnostic databases General diagnostic test data Specialized diagnostic data (e.g. STI clinics) Other data (e.g. blood donors)

5 STARHS methodologic issues Three major challenges to validity: Laboratory issues Data quality and completeness Selection bias

6 Laboratory issues Specimen quality Type of specimen Adequate quantity Collection, transport and storage

7 Laboratory issues Selection of test Vironostika,, BED, others Technical requirements & reproducibility Non-B viral subtypes Test performance Specificity and sensitivity Problem of late stage disease, ARVs and infant specimens

8 Data quality and completeness Missing and misclassified exposure category; critical! Need demographic data (gender, age, region) for stratified analysis Missing STARHS result

9 Data quality and completeness Availability of denominator data Data quality issues may be different Alternative techniques using HIV-positive results only under development at CDC

10 Exposure category classification according to HIV test requisition, returned questionnaires and modeled distribution, HIV-positives HIV test requisition Returned LES questionnaires among NIR Projected final distribution MSM MSM-IDU IDU Endemic HR hetero LR hetero Other NIR 1, ,049 54% 2% 9% 8% 6% 19% 1% % 3% 7% 27% 5% 16% 2% 2, % 2% 8% 18% 5% 18% 2% Total % NIR 4,471 54% 1, % 4, %

11 Addressing issues of incomplete or inaccurate data Risk factors incomplete assign NIR using weights from LES Risk factors inaccurate - reassignment using weights from LES STARHS result unavailable - assign based on proportions among known

12 Selection bias in the use of diagnostic data to calculate HIV incidence from STARHS Persons who test may not be representative of entire population Testing frequency may vary with HIV risk Seroconversion effect (SCE): Persons may test due to isolated high risk behaviours or symptoms associated with primary HIV infection

13 Representativeness Bias may be in either direction Some populations don t test due to perceived low risk (real or otherwise) High risk persons may not be prepared to accept possibility of HIV-positive result Not assessed quantitative impact of this issue Less of problem when most undergo testing (among MSM and IDU, probably >80%)

14 Testing frequency and risk Persons at highest HIV risk may test more frequently Impact would be to overestimate incidence Analysis of this issue in 2002 suggests not a major problem

15 Seroconversion effect Disproportionate proportion of recently infected persons test within STARHS window period Impact of this effect over-estimation of HIV incidence Empirical evidence of impact

16 Incidence calculated using different window periods with Vironostika assay, 2001 Incidence (per 100 person-years) MSM MSM-IDU IDU HR hetero LR hetero Window period (days)

17 Mean values of bias by SCE in presence of no, low and high interaction between inter-test interval and incidence density Ttest Itrue = None Parameter values SCE Minimum Mean Maximum Ttest - Itrue = Low Minimum Mean Maximum Ttest - Itrue = High Minimum Mean Maximum

18 Adjustment for SCE Developed formula which expresses measured HIV incidence as function of true incidence and SCE Calculated incidence with varied window period and fit to modeled incidence using formula incorporating P sce (proportion testing prematurely ) and I true (true incidence). Developed software with goodness-of-fit to identify values of P sce and I true which minimise sum of the squares of residuals between observed versus expected

19 Measured incidence as function of Psce and true incidence I est = N T obs T T test win Itrue + N Tobs Ttest Tobs ( N ( 1 (1 I ) ) + true Tobs ( N ( 1 (1 I ) ) P ) Twin true N sce T obs T T test win I true P sce

20 MSM: HIV incidence by six-month period and region,ontario, HIV incidence (per 100 py) Toronto Ottawa Rest of Ontario B 2000A 2000B 2001A 2001B 2002A 2002B 2003A 2003B Period

21 Crude and adjusted HIV incidence among MSM and IDU, Toronto, HIV incidence (per 100 py) MSMmeas MSMtrue IDUmeas IDUtrue Period

22 Conclusions Detection of recent infection using STARHS assay useful in measuring HIV incidence However, requires careful selection of study population, good quality data, and careful interpretation and control of biases Diagnostic data: due to missing and unrepresentative risk factor and HIV test history data, useful to enhance on an ongoing basis

23 Conclusions Goodness-of-fit approach allows adjustment to remove testing bias Modelled HIV incidence fit well to observed HIV incidence Adjusted incidence may be 50% lower than crude though bias appears to vary across exposure category, region and over time When possible, incidence derived from diagnostic HIV testing data should be presented with both crude and adjusted values

24 Acknowledgements At the HIV Laboratory: Lisa Santangelo,, data collection Lynda Healey, detuned assay Neil Hershfield custom software for incidence adjustment Core funding, Frank McGee, AIDS Bureau, OMHLTC Project funding Ontario HIV Treatment Network (start-up) Centre for Infectious Disease Prevention and Control, Health Canada (continued)